Mass event optimization
Hotspot LTE capacity with evolution to 5G
Nokia white paper Mass Event Optimization White Paper
Contents 1. Introduction
3
2. Mass event traffic profiles
3
3. LTE mass event solutions
6
4. LTE success cases
9
5. High capacity solutions in 5G
13
6. Mass event multicast experience in 5G
14
7. Conclusion
15
8. Further reading
15
9. Abbreviations
16
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1. Introduction Smartphones are great tools for sharing pictures or videos of music idols or sports stars at large mass events. At the same time, the heavy data traffic that develops in a small area poses a challenge for the management of radio network capacity. An additional challenge comes from the fact that traffic profiles are different during mass events compared to normal days. In particular, the networks tend to be uplink limited while also needing to carry a lot of signaling. This white paper illustrates the main characteristics of mass event traffic profiles, shows technical solutions for providing attractive end user performance, presents example success cases and considers evolution to 5G radio networks.
Figure 1: Mass events call for specific radio network solutions for providing consistent end user performance
2. Mass event traffic profiles Traffic in most mobile broadband networks is dominated by the downlink because of video streaming, with a typical downlink to uplink ratio being 10:1. This changes drastically during mass events and network capacity becomes limited by the uplink as participants take pictures and videos and upload them to social media. Downlink traffic is lower because there is little demand to watch streamed video content during a live event. A typical volume of uplink data during a mass event is several megabytes (MB) per person per hour, which is substantially more than during normal busy hours in the network. Also, call lengths tend to change during the mass event - the length of data calls increases while that of voice calls shortens. The traffic characteristics are summarized in Table 1.
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Normal day
Mass event
Downlink : uplink asymmetry
10:1 (downlink dominated)
1:1 .. 1:3 (uplink dominated)
Uplink data volume
<1 MB/person/hour
3-10 MB/person/ hour
Call length
Voice calls 2 min, data calls a few seconds
Voice calls get shorter, data calls get longer
Table 1: Traffic characteristics during mass events The downlink vs uplink asymmetry is illustrated in Figure 2. The data volume per subscriber per hour is up to 5 MB in the downlink and 0.5 MB in the uplink outside the mass event, while the downlink data volume drops during the event at 20:00 and the uplink volume grows considerably. In some events, the uplink volume may be three times greater than the downlink volume. The volume of data traffic grows every year. We have collected the average data volume in the uplink for a particular mass event in Asia in 2013, 2014 and 2015. The data volume for this event has grown from 65 kB per packet call (enhanced Radio Access Bearer, eRAB) to 130 kB and to 210 kB. This growth in data is driven by the ability of new smartphones to exchange and use high quality pictures and videos. The call length in the same mass event is illustrated in Figure 3. The data calls (non-Guaranteed Bit Rate non-GBR eRAB) lengthen during the event simply because the traffic volume in the uplink grows. At the same time, the length of voice call (QCI1 VoLTE) reduces. However, data calls are still considerably shorter than voice calls - just a few seconds compared to 1-2 minutes for voice calls. The inactivity time is not included in the data call length in this graph.
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Figure 2. #subs per cell DL Data Volume per Subs [MB] UL Data Volume per Subs [MB]
400
6.0 5.0
350
4.0
300 250
3.0
200
150
2.0
100
1.0
50 0
Data volume [MB]
Number of subscribers
450
0.0
Figure 3.
Figure Uplink (UL) vs downlink (DL) asymmetry changes during mass events © Nokia2: 2016
2
in session timer per ERAB, eRAB, QCI1 180
3.5
160
3.0
140 120
2.5
100
2.0
80
1.5
60
40
1.0
20
0.5
0
0.0
non-GBR [seconds]
QCI1 [seconds]
timerper perERAB, eRAB,non-GBR non-GBR in session time
© Nokia Figure 3:2016 eRAB session time changes during mass event (QCI1 = VoLTE call. Non-GBR = data call)
3
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3. LTE mass event solutions The main challenges of mass events relate to the uplink traffic, signaling and interference management. If the network experiences congestion, the applications tend to retry persistently, which can cause an avalanche of signaling and interference that degrades the throughput of the network. Solutions to improve end user performance include: • Centralized Radio Access Network (CRAN) for minimized uplink interference with multi-antenna reception • Multi-band idle mode load balancing • Automatic access class barring to maintain stable operation under extreme overload • Physical Downlink Control Channel (PDCCH) adaptation to prevent congestion of the control channel • Physical Uplink Control Channel (PUCCH) optimization to maximize the number of connected users • Uplink power control optimization to minimize interference • Traffic volume prediction for proper network dimensioning Mass events are usually plagued by inter-cell interference because it propagates well in the open area. Mobile transmission can create high inter-cell interference in the traditional RAN, leading to a situation where only a single cell receives the signal while the other cells receive just interference. A Centralized RAN brings a major benefit to the uplink because the mobile transmission is received by several RF units and is combined in the best way in the baseband. The Centralized RAN concept is illustrated in Figure 4, showing multiple RF heads connected to the common baseband pool. The Figure 4. the next section illustrate that Centralized RAN can increase the results in uplink capacity by two to three times.
Fiber
RF Heavy cell overlapping in open area
Baseband
4
© Nokia 2016
Figure 4: Centralized RAN solution Page 6
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Mass events use multiple frequencies to provide maximum capacity. Efficient network algorithms are required to balance the load between these frequencies. At the same time, excessive signaling should be avoided. The preferred solution is based on idle mode load balancing. When the Radio Resource Control (RRC) connection is released, the network can guide the device to another frequency to balance the loading. There is no urgent need to balance the loading of the RRC-connected devices because the typical RRC connection is very short. It is enough to run the load balancing actions during the release Figure 5. of the connection. The solution is shown in Figure 5 and the benefits are illustrated in Figure 6. The idle mode load balancing is enabled at sample 27 and disabled at sample 40. Band
Number of connected UEs
2600 2100 1800
Load balancing in RRC connection release
800
Figure 6.
Figure 5: Idle mode load balancing solution
200000 180000 160000 140000 120000 100000 80000 60000 40000 20000 0
High band (10MHz)
© Nokia 2016
Sample 49
Sample 46
Sample 43
Sample 40
Sample 37
Sample 34
Sample 31
Sample 28
Sample 25
Load balancing disabled
Sample 22
Sample 19
Sample 16
Sample 13
Sample 7
Sample 10
Load balancing enabled
Sample 4
5
Sample 1
Number of call setup attempts
Low band (10MHz)
6 © Nokia6: 2016 Figure Idle mode load balancing benefits
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Optimization of signaling capacity is critical in mass events. If the signaling or connected user capacity is exhausted, the amount of interference and signaling can increase sharply, degrading the network performance. It is important to consider the optimization of PDCCH and PUCCH capacity to avoid PDCCH congestion by applying aggregation and boosting transmission power. High levels of aggregation can provide excellent reliability but it can also eat into PDCCH resources, causing signaling congestion. Uplink PUCCH is required to carry feedback signaling, for example Channel Quality Indicator (CQI). PUCCH can also be a bottleneck, restricting the number of connected users. Its configuration and dimensioning must be optimized to maximize the number of users. Optimization is concerned with PUCCH size and CQI frequency - a longer CQI period of 40 or 80 ms decreases the consumption of PUCCH capacity and allows the maximum number of connected users. Control channel congestion can be measured via the utilization of the Control Channel Element (CCE), which should remain well below 100 percent. If the amount of traffic greatly exceeds the network capacity, it is important to manage the overload and avoid signaling congestion. If there is an avalanche of retries by smartphone applications, signaling can explode, leading to high interference levels and low network utilization. Signaling congestion can be avoided by automatic access barring. When the cell is subject to a high signaling load, the network gives a probability value for each access class so that only some devices are allowed to send RRC connection requests. This solution does not require a separate access class but all devices can use the same access class. The solution is dynamic and every device will be served eventually. The network efficiency improves when unnecessary signaling can be avoided. Uplink power control in LTE has more flexibility than in WCDMA because of intra-cell orthogonality. LTE power control still needs to be optimized to minimize the inter-cell interference, particularly in open areas of mass events. The lessons learned are power control needs to be configured conservatively - preferably in open loop mode instead of closed loop mode, the signal level target should be relatively low and only partial compensation of the path loss is needed to minimize the interference generated. Figure 7 illustrates the amount of signaling and the uplink interference levels. There is a clear correlation. The power control parameters have been properly configured in this example since the interference was increased by only 5 dB even under extreme loading.
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Figure 7. Avg RSSI PUSCH, LTE_5444B Uplink interference
25,00,000
RRC attempts
20,00,000 15,00,000
-96 -97
-98 -99
10,00,000 5,00,000 0
7
-95
-100
dBm
RRCattempts setup attempts LTE_753C RRC
-101 -102 -103
© Nokia 2016
Figure 7: Correlation between signaling and uplink interference The network dimensioning for mass events could consider the traffic prediction from the earlier events. The general traffic growth is more than 50 percent per year, which needs to be considered in the event dimensioning. If the network is under-dimensioned, the end user performance will degrade even if the network is properly optimized. Assuming 50,000 participants and 35 percent operator market share and 5 MB/person/hour leads to 88 GB/hour uplink traffic volume. Assuming uplink spectral efficiency of 1 bps/Hz/cell, this gives a maximum of 9 GB/hour with a 20 MHz cell. Even under very ideal traffic distribution between cells, we would need 10 cells at 20 MHz or 20 cells at 10 MHz. In practice, even more cells are required since the traffic is never ideally distributed between them.
4. LTE success cases This section illustrates a few examples of excellent mass event performance achieved with optimization solutions. The benefits of Centralized RAN are shown in Figure 8 and in Figure 9. The statistics are taken from a football game in Europe where CRAN was off during the first half and on during the second half. The uplink data volume grew by a factor of 2.2, while the PRB utilization decreased by 38 percent, corresponding to a gain in uplink efficiency of 3.5. The massive benefit comes from the combination of the signal from the multiple RF heads boosting signal levels and minimizing the interference.
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Figure 8. Uplink data volume 9000 8000 7000
MB/15 min
6000
5000 4000 3000 2000 1000 0
Figure 9.
CRAN off
CRAN on
Figure 8: The benefit of Centralized RAN for uplink data volume 8
© Nokia 2016
Uplink PRB usage 35%
PRB usage
30% 25% 20%
15% 10% 5% 0
CRAN off
CRAN on
Figure 9: The benefit of Centralized RAN for uplink PRB usage 9 © Nokia 2016 Figure 10 illustrates a huge data volume from a mass event in Asia. The uplink data volume also exceeds the downlink volume in this event. The uplink data peaked at 430 GB per hour during the event, corresponding to approx. 1 Gbps average data rate. The downlink data peaked at 600 GB per hour just before the main event. Figure 11 shows the number of packet calls (enhanced Radio Access Bearer, eRAB) during the same event. The peak hour experienced more than three million packet calls per hour, corresponding to nearly one packet call every millisecond. Page 10
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Figure 10. DL data volume [MB], event day
UL data volume [MB], event day
7,00,000
Total Datavolume [MB]
6,00,000
5,00,000 4,00,000 3,00,000 2,00,000 1,00,000 0
Figure 11. 10 © Nokia 2016
12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00
Figure10: Data volume in a mass event eRAB Setup Attempts per hour
3500000 3000000 2500000 2000000 1500000 1000000
23:00
22:00
21:00
20:00
19:00
18:00
17:00
16:00
15:00
14:00
13:00
12:00
11:00
9:00
10:00
8:00
7:00
6:00
5:00
4:00
3:00
2:00
1:00
0
0:00
500000
© Nokia 2016 Figure11: Packet call attempts during a mass event
11
Control plane congestion can be measured through Control Channel Element (CCE) utilization, which is illustrated as a function of uplink PRB utilization as shown in Figure 12. The target is to ensure that the control channel is not the limiting factor in the system. The design has been successful since the CCE utilization peaks at 70 percent when the uplink PRB utilization hits 100 percent.
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Figure 12. 100%
CCE Utilization
80%
60%
40%
20%
0% 0
20
40
60
80
100
UL PRB Utilization [%] 12
© Nokia 2016
Figure12: Control Channel Element (CCE) utilization The setup success rate for voice (VoLTE) calls is shown in Figure 13. The performance was excellent at more than 99.5 percent success rate, even during the Figure 13.event peak hour. VoLTE calls have higher priority than data calls, but the prioritization only works properly if the signaling and interference can be managed efficiently. VoLTE setup success rate 100.0 99.0 98.0 97.0 96.0 95.0 94.0 93.0 92.0
91.0 00:00 01:00 02:00 03:00 04:00 05:00 06:00 07:00 08:00 09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00
90.0
13
© Nokia 2016 Figure13: VoLTE setup success rate in a mass event
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5. High capacity solutions in 5G LTE radio still has much room for growth in capabilities, spectrum usage and cell density. LTE-Advanced Pro is the next phase of LTE evolution, taking LTE capabilities closer to 5G targets. 5G radio will provide a massive boost in both data rates and hot spot capacity for the next decade. The improvement comes from two factors, larger bandwidth and higher base station density. Figure 14 illustrates the hot spot capacity in terms of Gbps per km2 with the different spectrum options. The assumptions are listed in Table 2. The starting point is a typical LTE deployment with 20 sites per km2 with 40 MHz of downlink spectrum. We assume spectral efficiency of 2.0 bps/Hz/cell and a traffic distribution factor of 4.0, which means that the highest loaded cell carries four times more data than the average cell. This deployment provides a capacity of 1 Gbps/km2. The capacity can be increased with 5G or LTE by using all the spectrum below 6 GHz, including unlicensed bands, by increasing the site density to 50/km2 and by using new LTE evolution and 5G features to boost spectral efficiency. We assume that the traffic distribution factor increases with higher site density because the traffic will likely become less equally distributed in the small cells. This scenario can provide up to 10 Gbps/km2. A further boost to capacity can be obtained by using centimeter waves where a lot more spectrum is available. The site density needs to be high because of the propagation characteristics at high frequencies. The cm-wave scenario with 600 MHz of spectrum can provide 100 Gbps/km2. Using millimeter waves brings even more spectrum and a higher site density, making 1 Tbps/km2 possible. That is a huge capacity when we consider that the total amount of mobile data in China is currently a few Tbps for the whole country for all operators together, and below Tbps in most small countries. The aim in 5G is to provide such high capacity in one square kilometer, not for the whole country. LTE today
LTE/5G sub 6 GHz 5G at cm waves
5G at mm waves
Bandwidth
40 MHz
200 MHz
600 MHz
2000 MHz
Site density
20/km2
50/km2
150/km2
300/km2
Sectors per site
2.5
2.5
3.0
4.0
2.0 bps/Hz/cell
4.0 bps/Hz/cell
6.0 bps/Hz/cell
6.0 bps/Hz/cell
4.0
10.0
15.0
15.0
1.0 Gbps/km2
10 Gbps/km2
108 Gbps/km2
960 Gbps/km2
Spectral efficiency Traffic distribution factor Resulting traffic density
Table 2: Assumptions for 5G capacity evaluation Page 13
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Figure 14. Spectrum [MHz]
Per operator in downlink
5G at mm
2000 MHz
5G at cm 5G/LTE at <6 GHz
600 MHz
200 MHz
40 MHz
LTE today
100 Gbps /km2
10 Gbps /km2
1 Gbps /km2 20/km2
>1 Tbps /km2
Site density [/km2] 50/km2
150/km2
300/km2
Figure 14: Hot spot capacity with 5G centimeter and millimeter waves 14 © Nokia 2016
6. Mass event multicast experience in 5G The impressive capabilities of 5G make it possible to enhance the customer stadium experience still further. 5G can augment the real stadium experience with live video feeds from different camera positions without any delay. Users could even switch the camera angle and get a truly instant replay. The video would also be in 4K or 8K (HD or UHD quality). Zero-delay augmented reality will free event visitors from their fixed seat. For a great user experience, the real world and 4K/8K multicast video are in instantaneous synchronization. This could form the basis for a new paid service for event attendees, particularly those far from the action, generating revenue for the operator and event organizer. Such a mass event experience is enabled by live multi-cast synchronous and instantaneous data transmission across a large number of devices. Nokia demonstrated such a 5G multicast experience at the Mobile World Congress in Barcelona in 2016. This is illustrated in Figure 15.
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Figure 15.
Multi-cast system Low latency frame structure
Reliable, synchronous, zero latency multi-cast
15
© Nokia 2016
Figure 15: Low latency 5G multicast experience at stadium
7. Conclusion Designing radio networks for mass events requires special attention to providing an attractive end user performance. Networks tend to be uplink limited during mass events and the uplink data volume per subscriber can increase by a factor of 10. Combined with a high density of people in a small open area, this makes network design a challenge. Nokia provides solutions for boosting mass event performance. Centralized RAN triples uplink capacity by combining signals and by minimizing interference. Other solutions are dynamic load balancing and control channel optimization. A few success cases show more than 1 Gbps combined uplink throughput in a mass event and with more than three million packets calls per hour while still providing excellent success rates. 5G radio can substantially increase the capacity up to 1 Tbps per km2 in hot spots. 5G opens completely new capabilities to enjoy stadium events with a low latency multicast experience, where participants can get virtual zero latency access to different cameras and viewpoints.
8. Further reading • • • • • •
Nokia 5G innovations Nokia Pop-up Network Mass event solutions Mass event white paper 5G stadium LTE-Advanced Pro
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9. Abbreviations CCE
Control Channel Element
CQI
Channel Quality Indicator
CRAN
Centralized Radio Access Network
eRAB
Enhanced Radio Access Bearer
LTE
Long Term Evolution
MIMO
Multiple Input Multiple Output
PDCCH
Physical Downlink Control Channel
PRB
Physical Resource Block
PUCCH
Physical Uplink Control Channel
QCI
Quality of Service Class Identifier
RRC
Radio Resource Control
VoLTE
Voice over LTE
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Nokia is a registered trademark of Nokia Corporation. Other product and company names mentioned herein may be trademarks or trade names of their respective owners. Nokia Oyj Karaportti 3 FI-02610 Espoo Finland Tel. +358 (0) 10 44 88 000 Product code C401-012004-WP-201606-1-EN © Nokia 2016
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